Due to the Internet and wireless technology, data has never been more plentiful and available. Transactional applications such as ERP (enterprise resource planning), SCM (supply chain management), CRM (customer relationship management) and enterprise project management have matured and now gather large volumes of information about internal and external business processes. The gathering and use of unstructured data has also increased from the widespread use of web sites, email, knowledge management, XML (extensible markup language) and enterprise storage systems and will continue to do so as future applications are developed.
Unfortunately, having access to data is not the same as effectively using it. Users with the opportunity to analyze more data are often overwhelmed and frustrated by the amount of effort required to make sense of it all. Most organizations today use tools that were developed when networks and processors were slow, disk space was expensive and databases were unable to handle complex queries. These applications failed to present information clearly to business users when there were multiple dimensions of data to integrate into a decision.
Data in high-level summaries, such as simple dashboards, is presented in a rigid fashion and does not provide explanations of “why” results are as they appear. The drill-downs to detailed reports and associated search tools generate simple row and column views that have become long lists with text or numbers displayed out of context. More often than not, workers are unable to find answers to their questions through these systems alone. Because business people do not have a way to access and explore their data themselves, they usually end up either operating without the information or creating their own ad-hoc desktop solution.
Traditionally, business intelligence tools have attempted to accomplish this through end-user dashboards that link static reports and expose development tools. But simple dashboard gauges fail to capture complex business problems. At the same time, the number of columns and rows in static reports has grown well beyond end users' ability to quickly get meaning from the data. And, both dashboards and static reports fail to consider more than a few dimensions of data—thus failing to provide a true representation of today's more sophisticated business environments. Moreover, while graphical elements such as line and pie charts might be included in a static report, they display data in only one or two dimensions and cannot show relationships with data in other reports, which is undesirable.
The complexity of businesses has out-paced today's decision-making tools. As a result, organizations are struggling to make use of the volumes of information available to them. Workers spend too much time creating reports manually, and the growing list of custom reporting requests is overwhelming information technology (IT) staff. Moreover, the traditional means of generating reports and dashboards need to be extended to help users answer the complex questions that affect corporate performance. New solutions are required to keep pace with growing business complexity. It is not easy to create a self-service interface in which business users can intuitively explore and understand high volumes of data.
One attempt to overcome the above-noted problems is disclosed in U.S. Pat. No. 5,321,800. The '800 patent discloses an information presentation method for a subject being monitored. In the only illustrated embodiment, display segments of fixed size, shape and location are used to map out a human body (the subject) being analyzed by a physician or lab technician. Each portion of the body being monitored is associated with a datapoint. Rectangular-shaped icons are placed in the pre-defined segments in the human body display to show the status of the datapoint. The icons can have one of a plurality of colors. In addition, effects, such as changing the intensity of an icon's color, flashing/modulating the icon, and/or placing a different color in the center portion of an icon can also be used to provide status information.
The technique disclosed in the '800 patent, however, remains unsatisfactory for real time repetitive data analysis, particularly when there are numerous datapoints or subjects to monitor. For example, the technique is tied to the use of rectangular icons for conveying status information of every datapoint being evaluated. Because each icon has the same shape, the icons must be placed in specific locations to represent the datapoint of interest; this forces the observer to remember numerous datapoint-to-location correlations for a single subject (e.g., as shown in FIG. 3 of the '800 patent, the head portion alone contains 18 different datapoint locations). Moreover, if images for multiple subjects are displayed at the same time, it may be difficult to quickly determine the status of a particular datapoint or datapoints.
Accordingly, there is a need and desire for a technique that creates a suitable visual perspective of high volume, repetitive data that allows an observer to quickly determine the status of a particular subject (i.e., person, thing, business) being monitored even when multiple subjects are being monitored at the same time.